Digital Commons Network^™

Drought Response Of Trichloris Crinita Plants With Different Aridity History: Water Use, Leaf Elongation And Senescence, R. E. Quiroga, L. J. Blanco, R. A. Golluscio

IGC Proceedings (1977-2023)

No abstract provided.

Genetic Structure And Aflp Variation Of Six Native Festuca Hallii (Vasey Piper) Populations In The Northern Great Plains Of Canada, Jie Qiu, Yongbi Fu, Yuguang Bai, John F. Wilmshurst

IGC Proceedings (1977-2023)

No abstract provided.

Effect Of Sowing And Oversowing On Species Abundance In Mountain Pastures Of Central Italy, Andrea Pardini, F. Natali

IGC Proceedings (1977-2023)

No abstract provided.

Hydraulic Lift Through The Root Systems In Zygophyllum Xanthoxylum, Decao Niu, Xiaohong Xue, Shifang Pei, Hongrong Zhang, Hua Fu

IGC Proceedings (1977-2023)

No abstract provided.

Stage – Specific Predictive Models For Main Prognosis Measures Of Breast Cancer, Ahmed Attia Said, Laila A. Abd-Elmegid, Sherif Kholeif, Ayman Abdelsamie Gaber

Future Computing and Informatics Journal

Breast cancer is a malignant tumor that starts in the cells of the breast. A malignant tumor is a group of cancer cells that can grow into near tissues or invading the distant areas of the body. The disease occurs almost entirely in women, but men can get it, too. Survival rate, recurrence detection and disease-free survival rate (DFS) are the main patient's outcome and prognosis measures. Breast cancer outcomes are vary among different stages of the disease. There are five stages of breast cancer named as 0, 1, 2, 3, and 4. Prognosis helps doctors to save patients' lives …

Medical Image Retrieval Using Self-Organising Map On Texture Features, Shashwati Mishra

Future Computing and Informatics Journal

The process of capturing, transfer and sharing of information in the form of digital images have become easier due to the use of advanced technologies. Retrieval of desired images from these huge collections of image databases is one of the popular research areas and has its applications in various fields. An image set consists of images containing objects of different colours, shapes, orientations and sizes. The surface texture of the object in an image may also vary from another object in a different image. These factors make the process of image retrieval a difficult one. In this paper, Self-Organising Map …

A Genetic Algorithm For Service Flow Management With Budget Constraint In Heterogeneous Computing, Ahmed A. Abdulhamed, Medhat A. Tawfeek, Arabi E. Keshk

Future Computing and Informatics Journal

Heterogeneous computing supply various and scalable resources for many applications requirements. Its structure is based on interconnecting machines with several processing capacity spread over networks. The scientific bioinformatics and many other applications demand service flow processing in which services have dependencies execution. The environments of this computing are suitable for huge computational needs that contains diverse groups of services. Managing and mapping services of service flow to the suitable candidates who provides the service is classified as NP-complete problem. The managing such interdependent services on heterogeneous environments also takes the Quality of Service (QoS) requirements from users into account. This …

Partition Based Clustering Of Large Datasets Using Mapreduce Framework: An Analysis Of Recent Themes And Directions, Tanvir Habib Sardar, Zahid Ansari

Future Computing and Informatics Journal

Data clustering is one of the fundamental techniques in scientific analysis and data mining, which describes a dataset according to similarities among its objects. Partition based clustering algorithms are the most popular and widely used clustering technique. In this information era, due to the digitization of every field, the huge volume of data is available to data analysts. The quick growth of such datasets makes decade old computing platforms, programming paradigms, and clustering algorithms become inadequate to obtain knowledge from these datasets. To cluster such large datasets, Hadoop distributed platform, MapReduce programming paradigm and modified clustering algorithms are being used …

Bio-Inspired Computing: Algorithms Review, Deep Analysis, And The Scope Of Applications, Ashraf Darwish Prof.

Future Computing and Informatics Journal

Bio-inspired computing represents the umbrella of different studies of computer science, mathematics, and biology in the last years. Bioinspired computing optimization algorithms is an emerging approach which is based on the principles and inspiration of the biological evolution of nature to develop new and robust competing techniques. In the last years, the bio-inspired optimization algorithms are recognized in machine learning to address the optimal solutions of complex problems in science and engineering. However, these problems are usually nonlinear and restricted to multiple nonlinear constraints which propose many problems such as time requirements and high dimensionality to find the optimal solution. …

Task Schedul Ing For Cloud Computing Using Multi-Objective Hybrid Bacteria Foraging Algorithm, Sobhanayak Srichandan, Turuk Ashok Kumar, Sahoo Bibhudatta

Future Computing and Informatics Journal

Cloud computing is the delivery of computing services over the internet. Cloud services allow individuals and other businesses organization to use data that are managed by third parties or another person at remote locations. Most Cloud providers support services under constraints of Service Level Agreement (SLA) definitions. The SLAs are composed of different quality of service (QoS) rules promised by the provider. A cloud environment can be classified into two types: computing clouds and data clouds. In computing cloud, task scheduling plays a vital role in maintaining the quality of service and SLA. Efficient task scheduling is one of the …

An Analysis Of Mapreduce Efficiency In Document Clustering Using Parallel K-Means Algorithm, Tanvir Habib Sardar, Zahid Ansari

Future Computing and Informatics Journal

One of the significant data mining techniques is clustering. Due to expansion and digitalization of each field, large datasets are being generated rapidly. Such large dataset clustering is a challenge for traditional sequential clustering algorithms due to huge processing time. Distributed parallel architectures and algorithms are thus helpful to achieve performance and scalability requirement of clustering large datasets. In this study, we design and experiment a parallel k-means algorithm using MapReduce programming model and compared the result with sequential k-means for clustering varying size of document dataset. The result demonstrates that proposed k-means obtains higher performance and outperformed sequential k-means …

Tga: Team Game Algorithm, M.J. Mahmoodabadi

Future Computing and Informatics Journal

Lately, there is a growing interest in conducting research on optimization algorithms due to their wide range of engineering applications. One of the optimization algorithms' categories is evolutionary algorithms which are inspired from the natural behavior of animals and humans. Further, each of the evolutionary algorithms has its own advantages and disadvantages in convergence accuracy and computational time. In the present paper, a novel solution search algorithm taken from the team games is introduced. This evolutionary algorithm named Team Game Algorithm (TGA) involves passing a ball, making mistakes and substitution operators. Comparing the TGA's results to the outcomes of other …

Hybrid Energy Aware Clustered Protocol For Iot Heterogeneous Network, Rowayda A. Sadek

Future Computing and Informatics Journal

IoT diverse applications face many challenges. The main challenge is to have efficient energy aware communication protocols that utilize the diversity and heterogeneity of the connected things through Internet. Saving energy is a vital requirement in the limited battery energy nodes and also for the outsourced energy nodes for green computing. IoT milieu has many diverse devices that are heterogeneous in their energies, their Internet availability, etc. These devices are usually distributed into regions with different heterogeneity levels; ranging from homogeneous to near homogenous, till reaching to the high heterogeneous regions. Many existed protocols efficiently treated either the homogenous devices …

Attribute Selection Using Fuzzy Roughset Based Customized Similarity Measure For Lung Can Cer Microarra Y Gene Expression Data, C. Arunkumar, S. Ramakrishnan

Future Computing and Informatics Journal

Microarray gene expression data plays a prominent role in feature selection that helps in diagnosis and treatment of a wide variety of diseases. Microarray gene expression data contains redundant feature genes of high dimensionality and smaller training and testing samples. This paper proposes a customized similarity measure using fuzzy rough quick reduct algorithm for attribute selection. Information Gain based entropy is used to reduce the dimensionality in the first stage and the proposed fuzzy rough quick reduct method that defines a customized similarity measure for selecting the minimum number of informative genes and removing the redundant genes is employed at …

Classification Using Deep Learning Neural Networks For Brain Tumors, Heba Mohsen

Future Computing and Informatics Journal

Deep Learning is a new machine learning field that gained a lot of interest over the past few years. It was widely applied to several applications and proven to be a powerful machine learning tool for many of the complex problems. In this paper we used Deep Neural Network classifier which is one of the DL architectures for classifying a dataset of 66 brain MRIs into 4 classes e.g. normal, glioblastoma, sarcoma and metastatic bronchogenic carcinoma tumors. The classifier was combined with the discrete wavelet transform (DWT) the powerful feature extraction tool and principal components analysis (PCA) and the evaluation …

An Improved Rank Based Disease Prediction Using Web Navigation Patterns On Bio-Medical Databases, P. Dhanalakshmi, K. Ramani

Future Computing and Informatics Journal

Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the …

Informative Gene Selection Using Adaptive Analytic Hierarchy Process (A2hp), Abhishek Bhola, Shafa Mahajan

Future Computing and Informatics Journal

Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP). Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is …

A Nove L F U Z Z Y L O G I C B A S E D R Eve R S E E N G I N E E R I N G O F G E N E R Eg U L A T O R Y N E T W O R K, Raviajot Kaur, Abhishek Bhola, Shailendra Singh

Future Computing and Informatics Journal

Genes of an organism play a very crucial role in the working of various cellular activities. Genes and other biological molecules like DNA, RNA do not operate alone but they all are correlated. Their relationships are shown with the help of networks commonly known as Gene Regulatory Networks. Gene Regulatory Networks are complex control networks that show the map of interactions among the genes. They provide very useful contribution to the genomic science and increase the understanding of various biological processes. In this paper, fuzzy logic based method is proposed for the reverse engineering of gene regulatory network from microarray …

Lawrence University One Hundred Seventy-First Commencement, Sunday, June 14, 2020, Lawrence University

Commencement Programs

No abstract provided.

Protecting Minors With Substance Use Disorders: A Closer Look At The Relationship Of Confidentiality With Treatment Options, Katherine Slisz

Indiana Journal of Law and Social Equality

No abstract provided.

2020 Commencement Program And Video Highlights, Commencement

Commencement Archives 2020-29

The complete program for Portland State University's 2020 virtual Commencement ceremonies.

Streaming video (.mp4, 32 minutes) includes Portland State University congratulations and messages from the President, Provost, Board of Trustees, Alumni Association, and keynotes from a graduate and faculty member.

Using Group Affinity To Predict Community Formation In Social Networks, Joseph Leung

Undergraduate Honors Theses

A well-studied topic in network theory is detecting the communities found in real-world networks. Community detection is a technique to better understand the way in which small dense substructures appear in these networks. Such substructures can often tell important information about groups that form in such systems. A prominent feature of many networks is that they evolve over time, forming and dissolving new edges between different nodes that appear. In this thesis, we consider how we can use the community structure of a network at a certain point in time to predict the state of a network’s communities at some …

2020-06-12/13/14 Daily Unm Global Health Covid-19 Briefing, Christophe G. Lambert, Shawn Stoicu, Ingrid Hendrix, Lori D. Sloane, Anastasiya Nestsiarovich, Praveen Kumar, Nicolas Lauve, Jenny Situ, Clinton Onyango, Perez Olewe, Cristian Bologa, Orrin Myers, Douglas J. Perkins

HSC Covid 19 Briefings

Executive Summary:

NM Highlights: NM case count. Increased road travel. ABQ ART to resume. Film industry to reopen. US Highlights: Policy advocacy to end mass Incarceration. International Highlights: COVID-19 cases in Italy. Temperature checks at Canada airports. Economics, Workforce, Supply Chain, PPE: Epidemiology Highlights: Mask stability. Supply operations management. Masks going to transport companies. Digital tools for awareness. Customers like clean stores. Epidemiology: Michigan hospitalization risk factors. Ranking the risks of reopening. Pandemic growth rate scaling. Outbreak detection and contract tracing. Worldwide mortality report. Screening pregnant women. Social learning model for pandemics. Healthcare Policy Recommendations: Re-opening of sports centers. Minimize …

Ecology Of Herbaceous Legumes In The Fortescue River Valley Floodplain, Western Australia, Dion Nicol, J. E. D. Fox

IGC Proceedings (1977-2023)

No abstract provided.

The Effect Of Annual Weather On Spring Grass Phenological Development, G. Nagy, K. Petö

IGC Proceedings (1977-2023)

No abstract provided.

Does Disturbance Similarly Facilitate Weed Invasion Within Grass, Forb, And Shrub Plots?, Tom A. Monaco, E. D. Leonard

IGC Proceedings (1977-2023)

No abstract provided.

Infant Attraction: Why Social Bridging Matters For Female Leadership In Tibetan Macaques, Xi Wang, Dong-Po Xia, Lixing Sun, Paul A. Garber, Randall C. Kyes, Lori K. Sheeran, Bing-Hua Sun, Bo-Wen Li, Jin-Hua Li

Biology Faculty Scholarship

Leadership is a key issue in the study of collective behavior in social animals. Affiliation–leadership models predict that dyadic partner preferences based on grooming relationships or alliance formation positively affect an individual’s decision to follow or support a conspecific. In the case of many primate species, females without young infants are attracted to mother–infant dyads. However, the effects of mother–infant–female associations on affiliation–leadership models remain less clear. In free-ranging Tibetan macaques Macaca thibetana, we used social network analysis to examine the importance of “mother-infant-adult female” social bridging events as a predictor of who leads and who follows during group …

Transcriptome Studies On The Toxicity Of Silica Nanoparticles, Shih-Yi Hsu

USF Tampa Graduate Theses and Dissertations

Nanotechnology enables more precise harmony in health condition via reducing the dosage amount, improving the delivery of hydrophobic drugs, more specific targeting to the cancerous sites, and so on. Nevertheless, issues regarding the toxicity of nanotechnology have begun to call for attention several decades later after the innovation of nanotechnology. Tools about risk management of nanotechnology have been developed, but recently not much evidence recognizes the toxicity of nanoparticles (NPs) except for some animal studies, which demonstrated organ damage after the exposure to NPs. Toxicogenomic approach refers to the method utilizing gene expression to evaluate the chemical toxicity. Databases as …

A Review Of Methodologies Applied For Determining Particulate Matter Characterization In Urban Regions, Garrett F. Diehl

University Honors Theses

This is a literature review on previous research conducted on particulate matter deposited on urban vegetation. This was accomplished by searching six databases, that uncovered 37 peer-reviewed journal articles. The main objective of this review is to present the methodology and findings of the articles analyzed to demonstrate how research in this area of study is being conducted. The findings show that there are variations in the literature and that many variables are not being incorporated into the methods and analyses of particulate matter found on urban vegetation. Understanding how different studies have analyzed particulate matter found on urban vegetation …

Molecular Mechanisms And Immunomodulatory Effects Of Platinum Analogs On Some Genes And As Anticancer Drugs: Review Article, Dalia Abdalkader Shakur, Suhad Hatem Al-Mugdadi

Muthanna Medical Journal

Platinum analogs includes cisplatin, oxaliplatin and carboplatin. Cisplatin is a chemotherapeutic drugwith excellent success in the management of human malignancies. Molecular mechanism of actionrelated to its capacity to crosslink of DNA purine bases; also, by interfere with DNA repair, leading toDNA break, and consequently lead to apoptosis in cancer cells. Cisplatin also found to haveimmunomodulatory properties besides its cytotoxic effect.